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» An Approach to Classify Semi-structured Objects
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CVPR
2010
IEEE
13 years 5 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk
ECCV
2008
Springer
14 years 9 months ago
Beyond Nouns: Exploiting Prepositions and Comparative Adjectives for Learning Visual Classifiers
Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
Abhinav Gupta, Larry S. Davis
SIGIR
2003
ACM
14 years 29 days ago
A maximal figure-of-merit learning approach to text categorization
A novel maximal figure-of-merit (MFoM) learning approach to text categorization is proposed. Different from the conventional techniques, the proposed MFoM method attempts to integ...
Sheng Gao, Wen Wu, Chin-Hui Lee, Tat-Seng Chua
ICPR
2000
IEEE
14 years 8 months ago
Invariant Image Object Recognition Using Mixture Densities
In this paper we present a mixture density based approach to invariant image object recognition. We start our experiments using Gaussian mixture densities within a Bayesian classi...
Daniel Keysers, Hermann Ney, Jörg Dahmen, Mar...
KDD
2002
ACM
119views Data Mining» more  KDD 2002»
14 years 8 months ago
Evaluating classifiers' performance in a constrained environment
In this paper, we focus on methodology of finding a classifier with a minimal cost in presence of additional performance constraints. ROCCH analysis, where accuracy and cost are i...
Anna Olecka